This is good. It seems to me the limiting variable for a company to commercialize this would be access to data and expertise at the intersection of AI/Chip Design. Any other bottlenecks you see?
Customer base is a big one. Limited number of people you can serve (although this becomes a bit better when you remember that these customers are whales that will pay multiple firms for their research/testing).
Also- the overlooked player that makes all this happen is HPC, and that's not something many people can do well (it's a very new field). Scale is itself a huge player that can change equations (which is why Deep Learning fell in love with it). Spoiler alert- I'm working on something related to AI and HPC for chips soon.
Edge-GNN is so cool.
Edges aggregate information from nodes.
The nodes then aggregate neighbouring nodes along with edge embeddings.
Domain knowledge resulting in minor changes to a model goes a long way indeed!
yep
Great content once again. Makes you get a glimpse into the chip wars that are about to heat up seriously
Exciting stuff
This is good. It seems to me the limiting variable for a company to commercialize this would be access to data and expertise at the intersection of AI/Chip Design. Any other bottlenecks you see?
Customer base is a big one. Limited number of people you can serve (although this becomes a bit better when you remember that these customers are whales that will pay multiple firms for their research/testing).
Also- the overlooked player that makes all this happen is HPC, and that's not something many people can do well (it's a very new field). Scale is itself a huge player that can change equations (which is why Deep Learning fell in love with it). Spoiler alert- I'm working on something related to AI and HPC for chips soon.